Biography

Dr. Jibin Wu is an Assistant Professor jointly appointed in the Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University. Before joining PolyU, he was a research scientist at Sea AI Lab (SAIL) from 2021 to 2022. Dr. Wu received Bachelor and Ph.D. degrees from National University of Singapore (NUS) in 2016 and 2020, respectively.

Dr. Wu is currently affiliated with the MIND Lab@PolyU, which is dedicated to advancing the frontiers of nature-inspired artificial intelligence research. His research interests encompass a wide range of areas, focusing on brain-inspired computing, large foundation models, and speech processing. His primary dedication lies in unraveling the computational principles and architectures of biological brains while also striving to develop cutting-edge cognitive machines that possess exceptional intelligence, energy efficiency, robustness, adaptability, and explainability.

Dr. Wu has actively published in prestigious conferences and journals in artificial intelligence and speech processing, including Nature Communications, TPAMI, TNNLS, TASLP, NeurIPS, ICML, and ICLR. He is currently serving as the Associate Editors for IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Cognitive and Developmental Systems.

Research Interests
  • Brain-inspired Computing

    Memory and Continual Learning, Reasoning, Brain-computer Interface, Spiking Neural Networks

  • Large Foundation Models

    Efficient Model Architecture Design, Multimodal Foundational Models, AI Agent, AI Infra

  • Speech Processing

    Hearing Aid Technology, Audio Language Models, Speech Enhancement

  • AI Hardware

    Hearing Aid, Smart Glasses

Education

  • Doctor of Philosophy, 2020

    National University of Singapore

  • BEng in Electrical Engineering, 2016

    National University of Singapore

Contact

Latest News

[06/2026] Congratulations to Yu Zhou for his paper “CausalBN-Bench: A Comprehensive Benchmark for Causal Learning Capability of LLMs” accepted by IEEE Transactions on Artificial Intelligence.
[06/2026] Congratulations to Xinyi Chen for her paper “PMSN: A Parallel Multi-compartment Spiking Neuron for Multi-scale Temporal Processing” accepted by IEEE Transactions on Neural Networks and Learning Systems.
[05/2026] Congratulations to Xinyi Chen for her paper “Temporal Structure Encoding Drives Accurate and Robust Temporal Processing in Spiking Neural Networks” accepted by IEEE Computational Intelligence Magazine.
[03/2026] Congratulations to Chenxiang Ma for his paper “Spatio-Temporal Decoupled Learning for Spiking Neural Networks” accepted by IEEE Transactions on Neural Networks and Learning Systems.
[02/2026] We have two papers accepted by CVPR 2026, titled “ReLaX: Reasoning with Latent Exploration for Large Reasoning Models” and “Temporal Interaction in Spiking Transformers with Multi-Delay Mixer”. Congratulations to Shimin Zhang, Xianwei Chen, Kexin Shi, and their coauthors.
[01/2026] We have three papers accepted by ICLR 2026, titled “Discovering heterogeneous synaptic plasticity rules via large-scale neural evolution”, “MindMix: A Multimodal Foundation Model for Auditory Perception Decoding via Deep Neural-Acoustic Alignment”, and “Advancing Spatiotemporal Representations in Spiking Neural Networks via Parametric Invertible Transformation”. Congratulations to Ziyuan Ye, Rui Liu, Yinsong Yan, and their coauthors.
[01/2026] We have two papers accepted by ICASSP 2026, titled “Towards Efficient Spiking Neural Networks: A Reliable Structured Pruning Criterion” and “CSC-AADNet: Addressing Cross-Subject and Cross-Scenario Challenges in EEG-Based Auditory Attention Decoding” . Congratulations to Hanwen Liu, Zhige Chen, and their coauthors.

Services

Associate Editor
IEEE Transactions on Neural Networks and Learning Systems
Associate Editor
IEEE Transactions on Cognitive and Developmental Systems
Associate Editor
IEEE Transactions on Computational Intelligence Letters
Executive Committee Member
IEEE (Hong Kong) Computational Intelligence Chapter

Research Team

Postdoc Fellows

Rui LIU

Research Interests

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Neuroimaging Analysis

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Multimodal Foundation Model

Xinyi CHEN

Research Interests

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Brain-inspired Computing

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Spiking Neural Network

PhD Students

Shu PENG

Research Interests

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Brain Computer Interface

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EEG Foundation Models

Zehao LIU

Research Interests

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Large Foundation Model

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Machine Learning System

Chengzhi JI

Research Interests

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Large Foundation Model

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Memory Models

Ling Wang

Research Interests

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Multimodal Foundation Model

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Active Perception

Hanglei ZHANG

Research Interests

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Audio Language Model

Shimin ZHANG

Research Interests

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Reasoning

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Speech Processing

Yufei ZHANG

Research Interests

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Audio-Visual Processing

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Time-series Analysis

Ruofan YAN

Research Interests

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Brain-computer Interface

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Computational Audition

Zhige CHEN

Research Interests

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Brain-computer Interface

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Large Foundation Models

Xianwei CHEN

Research Interests

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AI Agent

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Embodied Intelligence

Yuhong CHOU

Research Interests

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Efficient LLM

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AI Infra

Beichen HUANG

Research Interests

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Evolutionary Computation

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Neural Evolution

Yinsong YAN

Research Interests

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Brain-inspired Computing

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Multimodal Foundation Model

Yu ZHOU

Research Interests

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Large Foundation Models

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Deep Reinforcement Learning

Ziyuan YE

Research Interests

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Learning and Memory

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Large Foundation Models

Xiang HAO

Research Interests

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Speech Processing

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Hearing Aid Technology

Chenxiang MA

Research Interests

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Spiking Neural Network

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Local Learning

Mphil Student

Qiyuan Sun

Research Interests

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Speech Processing

Research Assistants

Mengqi XU

Research Interests

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Machine Learning

Alumni

Qu YANG
Ph.D. Student2020 - 2024
AI Researcher, Huawei (Singapore)
Song Zeyang
Ph.D. Student2021 - 2026
Senior Researcher, Tecent (Singapore)

Award

Best Paper Award
The International Conference on Machine Intelligence and Nature-inspireD Computing (MIND 2025) 2025
First Prize with Cash Prize of USD 15,000
IEEE CIS FLAME Technical Challenge 2024 2024
Best Paper Award
IEEE Conference on Artificial Intelligence 2024
Track 1 (Algorithmic) Winner with Cash Prize of USD 15,000
Intel Neuromorphic Deep Noise Suppression Challenge 2023
Second Prize of Final Contest with Cash Prize of RMB 60,000
International Collegiate Competition for Brain-inspired Computing 2019
Tsinghua University, China (Team Leader)
President’s Graduate Fellowship
National University of Singapore 2019 – 2020
First Prize of Final Contest with Cash Prize of RMB 100,000
International Collegiate Competition for Brain-inspired Computing 2018
Tsinghua University, China (Team Leader)

Recent Publications

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Yu Zhou, Xingyu Wu, Jibin Wu, Liang Feng, Kay Chen Tan (2026). CausalBN-Bench: A Comprehensive Benchmark for Causal Learning Capability of LLMs. IEEE Transactions on Artificial Intelligence.

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Siying Liu, Zikai Wang, Hanle Zheng, Yifan Hu, Xilin Wang, Qingkai Yang, Jibin Wu, Hao Guo, Lei Deng (2026). ISTASTrack: Bridging ANN and SNN via ISTA Adapter for RGB-Event Tracking. in IEEE Transactions on Image Processing.

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Chenxiang Ma, Xinyi Chen, Kay Chen Tan, Jibin Wu* (2026). Spatiotemporal Decoupled Learning for Spiking Neural Networks. in IEEE Transactions on Neural Networks and Learning Systems.

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Xinyi Chen, Yinsong Yan, Hanwen Liu, Malu Zhang, Yujie Wu, Qinyuan Ren, Huajin Tang, Kay Chen Tan, Jibin Wu* (2026). Temporal Structure Encoding Drives Accurate and Robust Temporal Processing in Spiking Neural Networks. in IEEE Computational Intelligence Magazine.

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Xun Zhou, Songbai Liu, Jibin Wu, Yue Wang, Kay Chen Tan (2026). From Coarse to Fine A Multi-Stage Framework for Neural Architecture Search. in IEEE Computational Intelligence Magazine.

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